Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Multi-Step Inference for Reasoning over Paragraphs
Complex reasoning over text requires understanding and chaining together free-form predicates and logical connectives. Prior work has largely tried to do this either symbolically or with black-box…
MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics
Posing reading comprehension as a generation problem provides a great deal of flexibility, allowing for open-ended questions with few restrictions on possible answers. However, progress is impeded…
Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents
Images can give us insights into the contextual meanings of words, but current imagetext grounding approaches require detailed annotations. Such granular annotation is rare, expensive, and…
Grounded Compositional Outputs for Adaptive Language Modeling
Language models have emerged as a central component across NLP, and a great deal of progress depends on the ability to cheaply adapt them (e.g., through finetuning) to new domains and tasks. A…
Multilevel Text Alignment with Cross-Document Attention
Text alignment finds application in tasks such as citation recommendation and plagiarism detection. Existing alignment methods operate at a single, predefined level and cannot learn to align texts…
Parsing with Multilingual BERT, a Small Treebank, and a Small Corpus
Pretrained multilingual contextual representations have shown great success, but due to the limits of their pretraining data, their benefits do not apply equally to all language varieties. This…
Plug and Play Autoencoders for Conditional Text Generation
Text autoencoders are commonly used for conditional generation tasks such as style transfer. We propose methods which are plug and play, where any pretrained autoencoder can be used, and only…
The Multilingual Amazon Reviews Corpus
We present the Multilingual Amazon Reviews Corpus (MARC), a large-scale collection of Amazon reviews for multilingual text classification. The corpus contains reviews in English, Japanese, German,…
Writing Strategies for Science Communication: Data and Computational Analysis
Communicating complex scientific ideas without misleading or overwhelming the public is challenging. While science communication guides exist, they rarely offer empirical evidence for how their…
Do Language Embeddings Capture Scales?
Pretrained Language Models (LMs) have been shown to possess significant linguistic, common sense, and factual knowledge. One form of knowledge that has not been studied yet in this context is…